一种新的移动自组网局部时延相位转换方法
A New Phase Transition for Local Delays in MANETs
摘要：
我们认为移动自组织网络（MANET）的发射机位于根据泊松点在欧几里德平面，时隙Aloha介质访问（MAC）协议和所谓的中断的情况下，一个成功的传输需要一个信号干扰和噪声（SINR）大于一些阈值。我们分析了在这样的网络中的本地延迟，即节点发送数据包到其规定的下一跳接收器所需的时隙数。该分析在很大程度上取决于接收机的情况和衰落的可变性。在大多数情况下，每个节点具有有限平均的几何随机延迟，从而具有正的下一跳吞吐量。然而，空间（或大人口）平均这些个人有限的平均延迟导致无限的值在几个实际情况下，包括瑞利衰落和积极的热噪声的情况下。在某些情况下，它表现出一个有趣的相变现象，其中的空间平均值是有限的，当某些模型参数低于阈值和无限以上。我们称这种现象为竞争相变。我们认为，平均本地延迟的空间平均值是无限的，主要是因为中断逻辑，其中一个发送完整的数据包在时隙时，接收器被覆盖在所需的SINR和其中一个浪费所有其他时隙。这导致了“重新开始”机制，这反过来解释了为什么我们有无限的空间平均值。自适应编码提供了一种打破中断/重新启动逻辑的好方法。我们展示的例子中，平均延迟是有限的自适应编码的情况下，而他们是无限的中断的情况下。
英文摘要：
We consider Mobile Ad-hoc Network (MANET) with transmitters located according to a Poisson point in the Euclidean plane, slotted Aloha Medium Access (MAC) protocol and the so-called outage scenario, where a successful transmission requires a Signal-to-Interference-and-Noise (SINR) larger than some threshold. We analyze the local delays in such a network, namely the number of times slots required for nodes to transmit a packet to their prescribed next-hop receivers. The analysis depends very much on the receiver scenario and on the variability of the fading. In most cases, each node has finite-mean geometric random delay and thus a positive next hop throughput. However, the spatial (or large population) averaging of these individual finite mean-delays leads to infinite values in several practical cases, including the Rayleigh fading and positive thermal noise case. In some cases it exhibits an interesting phase transition phenomenon where the spatial average is finite when certain model parameters are below a threshold and infinite above. We call this phenomenon, contention phase transition. We argue that the spatial average of the mean local delays is infinite primarily because of the outage logic, where one transmits full packets at time slots when the receiver is covered at the required SINR and where one wastes all the other time slots. This results in the "RESTART" mechanism, which in turn explains why we have infinite spatial average. Adaptive coding offers a nice way of breaking the outage/RESTART logic. We show examples where the average delays are finite in the adaptive coding case, whereas they are infinite in the outage case.
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